A survey of automated visual inspection
Computer Vision and Image Understanding
Modeling visual attention via selective tuning
Artificial Intelligence - Special volume on computer vision
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
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In this paper, an improved paper defects detection method based on visual attention mechanism computation model is presented. First, multi-scale feature maps are extracted by linear filtering. Second, the comparative maps are obtained by carrying out center-surround difference operator. Third, the saliency map is obtained by combining conspicuity maps, which is gained by combining the multi-scale comparative maps. Last, the seed point of watershed segmentation is determined by competition among salient points in the saliency map and the defect regions are segmented from the background. Experimental results show the efficiency of the approach for paper defects detection.